Computed tomography-based deep learning and multi-instance learning for predicting microvascular invasion and prognosis in hepatocellular carcinoma

doi:10.3748/wjg.v31.i30.109186

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Aug 14, 2025 (publication date) through Aug 12, 2025

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World Journal of Gastroenterology

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1007-9327

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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World J Gastroenterol. Aug 14, 2025; 31(30): 109186
Published online Aug 14, 2025. doi: 10.3748/wjg.v31.i30.109186

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Figure 6 Kaplan-Meier curves of the hepatocellular carcinoma curative resection cohort and transcatheter arterial chemoembolization treatment cohort. A: Training set; B: Validation set; C: Transcatheter arterial chemoembolization treatment cohort. Each cohort showed that recurrence-free survival/progression-free survival of high-risk patients was significantly shorter than that of low-risk patients (P < 0.05). TACE: Transcatheter arterial chemoembolization.

Citation: Cen YY, Nong HY, Huang XX, Lu XX, Pu CH, Huang LH, Zheng XJ, Pan ZL, Huang Y, Ding K, Huang DY. Computed tomography-based deep learning and multi-instance learning for predicting microvascular invasion and prognosis in hepatocellular carcinoma. World J Gastroenterol 2025; 31(30): 109186
URL: https://www.wjgnet.com/1007-9327/full/v31/i30/109186.htm
DOI: https://dx.doi.org/10.3748/wjg.v31.i30.109186